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Retrieval of Green Tide Concentration and Interannual Variation Analysis in Yellow Sea Based on Multi-Source Remote Sensing Monitoring

机译:基于多源遥感监测的黄海绿潮浓度和依际变化分析的检索

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The economic losses and ecological damage caused by green tide in Yellow Sea have been very serious over the years, but the research on the risk of green tide is still in its infancy. The regional concentration is considered as a key factor in assessing the risk of green tides, because the harmful effects of the green tide come from the excessive accumulation and anoxia release of the decaying algae. Satellite remote sensing is recognized as the most effective means of monitoring the green tide. But different pixel resolution leads to inconsistence in multi-source satellite information fusion. In this paper, a general concentration retrieval model of green tide based on multi-source remote sensing monitoring is established for the disaster risk assessment and data fusion requirements in operational emergency. The model computes the green tide's concentration based on the minimum decision grid, which inputs the operational multisource satellite data, and outputs the green tide's concentration of any designated area such as coastal areas and some key areas of concern. Based on the proposed model, the paper computes the overall concentration of the green tide in Yellow Sea for 11 years since the occurrence year based on the operational multi-source satellite data. The results indicates that the interannual distribution of the green tide in Yellow Sea from 2008 to 2018 is generally on the rise, and the areas with higher concentration are distributed in the south coasts of Shandong Peninsula, China. Affected areas generally extend southward, and the center of the risk zone located parallel to the Yancheng and Lianyungang coasts of Jiangsu Province, pointing to the direction of Shandong Qingdao, China, and the risk becomes bigger from south to north.
机译:多年来,黄海绿潮造成的经济损失和生态损害已经非常严重,但对绿色潮汐风险的研究仍处于初期阶段。区域浓度被认为是评估绿色潮汐风险的关键因素,因为绿色潮汐的有害影响来自腐朽的藻类的过度积累和缺氧释放。卫星遥感被认为是监测绿色潮汐的最有效手段。但不同的像素分辨率导致多源卫星信息融合中的不一致。本文建立了基于多源遥感监测的绿色潮流的一般浓度检索模型,为操作紧急情况下的灾害风险评估和数据融合要求。该模型基于最小决策网格计算绿色潮流的浓度,该判决网格输入运营多源卫星数据,并输出绿色潮汐的任何指定区域,如沿海地区和一些关键领域。基于所提出的模型,自基于运营多源卫星数据的发生年度,本文基于拟议的模型,将黄海绿潮的整体浓度为11年。结果表明,从2008年到2018年的黄海绿潮处的年际分布一般在崛起,浓度较高的地区分布在中国山东半岛南海岸。受影响的地区一般展示南方,以及与江苏省盐城和连云港海岸平行的风险区的中心,指向山东青岛,中国的方向,南北风险变得越来越大。

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